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multi-atlas-segmentation

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Switch to unified view


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- A convenient tool to change the voxel dimension (field name: `pixeldim`) is: [`nifti_tool`](https://afni.nimh.nih.gov/pub/dist/doc/program_help/nifti_tool.html) from the [AFNI](https://afni.nimh.nih.gov/) package. Here is an example to change the input with incorrected voxel size (e.g. 1mm) into the correct one (0.1mm): `nifti_tool -mod_hdr -mod_field pixdim '0.0 0.1 0.1 0.1 0.1 0.1 0.1 0.1' -infiles $input_filename -prefix $output_filename`
- Sometimes, the image origin in the nifty head will be misplaced after the pixeldim change, which will make the affine registration fail (for both the mas_masking step and the mas_parcellation). A quick solution is to load the image into the [`NifTK`](https://github.com/NifTK/NifTK/releases), and "save as" a `.nii` or `.nii.gz` file, which will effectively reinitialize the image origin information int he nifti file header. We will post a more elegant solution with future update.


## Pipeline example


### pipeline demo
 
 A [demo script](demo/mas_demo.sh) is provided, which contains a complete end-to-end demonstration showing how to build and run the pipeline. It first download the atlas and test image from the [mouse brain atlas](https://github.com/dancebean/mouse-brain-atlas). It then run the following steps in sequential: brain extraction => N4 Bias Field Correction => brain structural parcellation (which itself consists of 3 sub-steps: atlas-to-test image registration (using dilated mask and bias-field-corrected brain image) -> atlas label propagation -> and multi-atlas label fusion).
  
### Function demo

	a/README.md		b/README.md
	...		...
89	- A convenient tool to change the voxel dimension (field name: `pixeldim`) is: [`nifti_tool`](https://afni.nimh.nih.gov/pub/dist/doc/program_help/nifti_tool.html) from the [AFNI](https://afni.nimh.nih.gov/) package. Here is an example to change the input with incorrected voxel size (e.g. 1mm) into the correct one (0.1mm): `nifti_tool -mod_hdr -mod_field pixdim '0.0 0.1 0.1 0.1 0.1 0.1 0.1 0.1' -infiles $input_filename -prefix $output_filename`	89	- A convenient tool to change the voxel dimension (field name: `pixeldim`) is: [`nifti_tool`](https://afni.nimh.nih.gov/pub/dist/doc/program_help/nifti_tool.html) from the [AFNI](https://afni.nimh.nih.gov/) package. Here is an example to change the input with incorrected voxel size (e.g. 1mm) into the correct one (0.1mm): `nifti_tool -mod_hdr -mod_field pixdim '0.0 0.1 0.1 0.1 0.1 0.1 0.1 0.1' -infiles $input_filename -prefix $output_filename`
90	- Sometimes, the image origin in the nifty head will be misplaced after the pixeldim change, which will make the affine registration fail (for both the mas_masking step and the mas_parcellation). A quick solution is to load the image into the [`NifTK`](https://github.com/NifTK/NifTK/releases), and "save as" a `.nii` or `.nii.gz` file, which will effectively reinitialize the image origin information int he nifti file header. We will post a more elegant solution with future update.	90	- Sometimes, the image origin in the nifty head will be misplaced after the pixeldim change, which will make the affine registration fail (for both the mas_masking step and the mas_parcellation). A quick solution is to load the image into the [`NifTK`](https://github.com/NifTK/NifTK/releases), and "save as" a `.nii` or `.nii.gz` file, which will effectively reinitialize the image origin information int he nifti file header. We will post a more elegant solution with future update.
91		91
92		92
93	## Pipeline example	93	## Pipeline example
94	### Processing pipeline schematic diagram
95	[![pipeline schematic](docs/journal.pone.0086576.g001.png) "Click here for the paper with detailed description of the processing pipeline"](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0086576)
96	### pipeline demo	94	### pipeline demo
97		95
98	A [demo script](demo/mas_demo.sh) is provided, which contains a complete end-to-end demonstration showing how to build and run the pipeline. It first download the atlas and test image from the [mouse brain atlas](https://github.com/dancebean/mouse-brain-atlas). It then run the following steps in sequential: brain extraction => N4 Bias Field Correction => brain structural parcellation (which itself consists of 3 sub-steps: atlas-to-test image registration (using dilated mask and bias-field-corrected brain image) -> atlas label propagation -> and multi-atlas label fusion).	96	A [demo script](demo/mas_demo.sh) is provided, which contains a complete end-to-end demonstration showing how to build and run the pipeline. It first download the atlas and test image from the [mouse brain atlas](https://github.com/dancebean/mouse-brain-atlas). It then run the following steps in sequential: brain extraction => N4 Bias Field Correction => brain structural parcellation (which itself consists of 3 sub-steps: atlas-to-test image registration (using dilated mask and bias-field-corrected brain image) -> atlas label propagation -> and multi-atlas label fusion).
99		97
100	### Function demo	98	### Function demo